MATLAB Deep Learning Toolbox
MATLAB Deep Learning Toolbox: A MATLAB-centered deep-learning environment with broad model, training, and deployment support. Ranked #9 of 35 in Deep Learning Software by our editors (6.6/10); pricing: 30-day trial; best for MATLAB users building and deploying deep-learning models.
At a glance
- Editor score6.6 / 10
- Pricing30-day trial
- Best forMATLAB users building and deploying deep-learning models
- Free planNo
- Training modeBoth
- Founded1984
- Facts checked23 Sep 2026
Where it wins
- Supports CNN, LSTM, GAN, and transformer network workflows
- Imports PyTorch, TensorFlow, and ONNX models and exports to TensorFlow or ONNX
- Offers multi-GPU, cluster, cloud training, compression, and code generation
Where it doesn't
- Requires MATLAB and Statistics and Machine Learning Toolbox
- GPU support additionally requires Parallel Computing Toolbox
- No free plan; the toolbox is available through paid licenses
Our verdict on MATLAB Deep Learning Toolbox
MATLAB Deep Learning Toolbox provides functions, apps, and Simulink blocks for designing, training, analyzing, and simulating deep neural networks. It is aimed at engineers and researchers already working in MATLAB, including teams that need to move models from experimentation toward desktop or cloud deployment. Network support covers CNNs, LSTMs, GANs, and transformers, while Deep Network Designer provides an interactive environment for editing and analyzing architectures. MATLAB and Python are supported, making the toolbox suitable for MATLAB-led workflows that also incorporate Python models.
Its ecosystem fit is a major strength. Models can be imported from PyTorch, TensorFlow, and ONNX, then exported to TensorFlow or ONNX for broader workflow compatibility. Simulink integration adds a path for simulation-oriented projects. Training workflows include image, video, and signal preparation, transfer learning with pretrained models, GPU and multi-GPU execution, clusters, and cloud workflows. Analysis tools visualize training progress and activations, while Grad-CAM, D-RISE, and LIME support result explanations. These capabilities make it a strong choice when model interoperability and engineering analysis matter alongside training.
Deployment depth further distinguishes the toolbox. Networks can be compressed through quantization, projection, or pruning, and trained models can generate C, C++, CUDA, or HDL code. The trade-off is a dependency-heavy, paid setup: licenses require MATLAB plus Statistics and Machine Learning Toolbox, and GPU workflows additionally require Parallel Computing Toolbox. A 30-day free trial is available, but there is no free plan. Choose it for MATLAB-centered teams needing integrated design, analysis, simulation, and deployment; teams seeking an open-source-first environment or a standalone deep-learning stack should consider alternatives.
MATLAB Deep Learning Toolbox pricing
All 2 MATLAB Deep Learning Toolbox plans and prices →
MATLAB Deep Learning Toolbox fact sheet
| Free plan | No |
|---|---|
| Paid from | Not verified |
| Training mode | Both |
| Deployment targets | Multiple |
| GPU acceleration | Yes |
| Distributed training | Yes |
| Supported languages | MATLAB, Python |
| Model formats | PyTorch, TensorFlow, ONNX |
| Free trial | 30 days |
| Deployment | Desktop, Cloud |
| Platforms | Windows, macOS, Linux |
| Support | Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 4 integrations: PyTorch, TensorFlow, ONNX, Simulink |
| Pricing | 30-day trial (source) |
| Website | mathworks.com |
| Facts checked | 23 Sep 2026 |
MATLAB Deep Learning Toolbox integrations
MATLAB Deep Learning Toolbox lists 4 integrations on its own site.
- PyTorch
- TensorFlow
- ONNX
- Simulink
Alternatives to MATLAB Deep Learning Toolbox
- Amazon SageMaker AIA comprehensive AWS-managed ML workflow suite for teams that accept usage-based billing.9.0
- Azure Machine LearningA paid Azure-native ML lifecycle service spanning automated training, deployment, and MLOps.7.8
- CaffeA free, established framework for teams maintaining Caffe-based model workflows.7.7
See all MATLAB Deep Learning Toolbox alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
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